restorePulseDashboardVersionRestore a previous version of a Duvo Pulse dashboard, making it live again (requires edit access). Non-destructive — it moves the head pointer to the chosen version.
| Name | Required | Description | Default |
|---|---|---|---|
| artifactId | Yes | ||
| revisionId | Yes |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Description goes beyond annotations by explaining the mechanism ('moves the head pointer') and confirming non-destructive behavior, which matches destructiveHint=false. Also mentions access control ('requires edit access'), adding useful operational context.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Two focused sentences with no filler. Front-loaded with the core action, then adds mechanism and access requirement. Every phrase contributes.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a 2-parameter action with no output schema, the description covers purpose, access, and mechanism. However, it omits parameter semantics and any return value indication, making it slightly incomplete but still adequate for a straightforward restore operation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, and the description provides no explanation of artifactId or revisionId. Though parameter names are fairly self-explanatory (dashboard ID and version ID), the description does not map them to the restoration action or clarify their roles, requiring inference.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb 'Restore', the resource 'previous version of a Duvo Pulse dashboard', and the outcome 'making it live again'. It distinguishes from sibling tools like getPulseDashboardVersionHtml (view-only) and updatePulseDashboard (modify current) by emphasizing the version-pointing action.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
Implies when to use (to revert to a prior version) and notes a prerequisite ('requires edit access'). It does not explicitly name alternatives or exclusions, but the context of version restoration vs current editing is clear from the description.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
Despite detailed descriptions, many tool names are highly ambiguous, with multiple tools covering the same conceptual actions (e.g., acceptClarityCaptureSuggestion vs. acceptClarityTeamAssignmentSuggestion, or the many deleteClarity*Interview tools). The set is so large that distinguishing between, say, listClarityFolders, listClarityProcesses, and listClarityProcessSummaries requires reading deep into descriptions, reducing agent selection accuracy.
The naming convention is predominantly verb_noun (e.g., createClarityProcess, listAgents, deleteQueue), and is remarkably consistent across the 316 tools. There are only minor deviations, such as 'fileSuggestedClarityProcesses' (verb + adjective noun) and 'bulkUpdateCasePriority' (where 'bulk' could be seen as a prefix), but overall the pattern holds strongly.
With 316 tools, this server is extremely oversized for any single agent to manage effectively. The massive number of tools suggests poor modularization—many of these tools likely belong in separate, smaller servers focused on specific domains (e.g., Clarity, Pulse, Agent management). The cognitive load for an agent to choose from 316 options is very high, leading to frequent misselection.
The tool surface covers an extraordinarily wide range of operations across the Duvo platform: agents, runs, cases, queues, Clarity processes, skills, integrations, notifications, teams, and more. Most resource types have full CRUD and lifecycle management. Notable minor gaps exist (e.g., no tools for managing specific notification batch severities dynamically, and some interview management is missing batch operations), but for the platform's scope, coverage is impressively thorough.